RACE (Remote Applications in Challenging Environments, http://www.race.ukaea.uk/) was founded in 2014 as part of the UK Atomic Energy Authority (UKAEA) fusion research and development programme - to create robots for operating in some of the most challenging environments imaginable. UKAEA’s wider mission is to lead the commercial development of fusion power and related technology, and position the UK as a leader in sustainable nuclear energy.
Based at Culham Science Centre near Oxford and at a new technology facility in South Yorkshire, UKAEA runs the UK’s fusion research programme and operates the Joint European Torus (JET) fusion experiment on behalf of scientists from 28 European countries. UKAEA is keeping the UK at the forefront of fusion as the world comes together to build the first powerplant-scale experiment, ITER – one step away from the realisation of nuclear fusion as a carbon-neutral energy source. JET serves as a test base for ITER, as well as future fusion demonstration powerplants putting electricity on the grid such as DEMO and UK’s own future STEP powerplant.
Future fusion power stations require efficient robotic servicing to guarantee safety and to maximise efficiency. Such devices are built to be run without direct human intervention, at best through sophisticated tele-operation. Many facilities are designed for human access rather than robot access, which limits the potential benefits of robotic systems. The concept of ‘Robot Accessibility’ is where assets and robots are designed to form a symbiotic relationship that maximises their useability. Where robots are used on existing infrastructure, it is important to understand what changes to either the environment or the robot need to be made for them to be successfully deployed.
A PhD studentship is available to carry out work on the following project:
This research will undertake in-depth user studies with asset designers and operators along with robot designers, to develop a set of guidelines about how facilities (and robots) could/should be designed to make the long-term deployment of fleets of residential robots feasible and maximise their impact. It is intended the research output would be a guidelines document similar to the UK governments document “The Building Regulations 2010 – Access to and use of buildings”
The primary use cases will be focused on nuclear fusion, however additional use cases in nuclear fission and potentially other application areas (such as offshore, agriculture, etc…) may also be explored.
The candidate will be working in the group of Dr Simon Watson and Dr Andy Weightman building on the expertise of control systems and reinforcement learning for robotic control.
The PhD-researcher will be embedded into the growing control and robotics group at the University of Manchester of more than 60 researchers, created through a set of significant UKRI/EPSRC grants (e.g. https://rainhub.org.uk/). The scholarship is part the strategic relationship between The University of Manchester and UKAEA. The student will be supervised by academics at the University of Manchester and RACE robotics experts.
Applicants should be educated to at least 1st Class/2:1 (or UK equivalent) BEng/MEng (Hons) level and will have a strong numerate, typically 1st, degree in engineering (electrical/electronic), mechanical engineering or mechatronics. A Master’s degree is desirable but not essential. The applicants should ideally have a background in/knowledge of engineering design.
Proposed start date: September 2022
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact. We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.
We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).